

import gc
import unittest

from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
		import jax
		import jax.numpy as jnp
		from flax.jax_utils import replicate
		from flax.training.common_utils import shard







@slow
@require_flax
class 					__lowercase  (						unittest.TestCase				):





							"""simple docstring"""

							def       snake_case			(					self						)		->       Tuple:
														# clean up the VRAM after each test
														super().tearDown()
														gc.collect()






							def       snake_case			(					self						)		->       Union[str, Any]:
														A      :					Any      		=					load_image(
														    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
														    '''/sd2-inpaint/init_image.png'''						)
														A      :					Optional[int]      		=					load_image(
														    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png'''						)

														A      :					Dict      		=					'''xvjiarui/stable-diffusion-2-inpainting'''
														A		,		A      :					List[str]      		=					FlaxStableDiffusionInpaintPipeline.from_pretrained(__UpperCAmelCase    ,						safety_checker=__UpperCAmelCase						)

														A      :					Tuple      		=					'''Face of a yellow cat, high resolution, sitting on a park bench'''

														A      :					List[Any]      		=					jax.random.PRNGKey(0						)
														A      :					Optional[int]      		=					50

														A      :					Union[str, Any]      		=					jax.device_count()
														A      :					Tuple      		=					num_samples * [prompt]
														A      :					List[str]      		=					num_samples * [init_image]
														A      :					Optional[int]      		=					num_samples * [mask_image]
														A		,		A		,		A      :					Optional[Any]      		=					pipeline.prepare_inputs(__UpperCAmelCase    ,						__UpperCAmelCase    ,						__UpperCAmelCase						)

														# shard inputs and rng
														A      :					Union[str, Any]      		=					replicate(__UpperCAmelCase						)
														A      :					Optional[Any]      		=					jax.random.split(__UpperCAmelCase    ,						jax.device_count()						)
														A      :					Any      		=					shard(__UpperCAmelCase						)
														A      :					Dict      		=					shard(__UpperCAmelCase						)
														A      :					str      		=					shard(__UpperCAmelCase						)

														A      :					Union[str, Any]      		=					pipeline(
														    __UpperCAmelCase    ,						__UpperCAmelCase    ,						__UpperCAmelCase    ,						__UpperCAmelCase    ,						__UpperCAmelCase    ,						__UpperCAmelCase    ,						jit=__UpperCAmelCase						)

														A      :					Tuple      		=					output.images.reshape(__UpperCAmelCase    ,						5_12    ,						5_12    ,						3						)

														A      :					List[str]      		=					images[0, 2_53:2_56, 2_53:2_56, -1]

														A      :					Dict      		=					jnp.asarray(jax.device_get(image_slice.flatten()						)						)
														A      :					Any      		=					jnp.array(
														    [0.3_6_1_1_3_0_7, 0.3_7_6_4_9_7_3_6, 0.3_7_5_7_4_0_8, 0.3_8_2_1_3_9_5_3, 0.3_9_2_9_5_1_6_7, 0.3_8_4_1_6_3_1, 0.4_1_5_5_4_9_7_8, 0.4_1_3_7_4_7_5, 0.4_2_1_7_0_8_4]						)
														print(f'output_slice: {output_slice}'						)
														assert jnp.abs(output_slice - expected_slice						).max() < 1E-2









import os
import unittest

from huggingface_hub.utils import are_progress_bars_disabled

import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enable_progress_bar







class 					__lowercase  (						unittest.TestCase				):





							"""simple docstring"""

							def       snake_case			(					self						)		->       Union[str, Any]:
														A      :					Dict      		=					logging.get_logger()

														# the current default level is logging.WARNING
														A      :					List[Any]      		=					logging.get_verbosity()

														logging.set_verbosity_error()
														self.assertEqual(logger.getEffectiveLevel()    ,						logging.get_verbosity()						)

														logging.set_verbosity_warning()
														self.assertEqual(logger.getEffectiveLevel()    ,						logging.get_verbosity()						)

														logging.set_verbosity_info()
														self.assertEqual(logger.getEffectiveLevel()    ,						logging.get_verbosity()						)

														logging.set_verbosity_debug()
														self.assertEqual(logger.getEffectiveLevel()    ,						logging.get_verbosity()						)

														# restore to the original level
														logging.set_verbosity(__UpperCAmelCase						)




							def       snake_case			(					self						)		->       str:
														A      :					Any      		=					logging.get_verbosity()

														A      :					Optional[Any]      		=					logging.get_logger('''transformers.models.bart.tokenization_bart'''						)
														A      :					Tuple      		=					'''Testing 1, 2, 3'''

														# should be able to log warnings (if default settings weren't overridden by `pytest --log-level-all`)
														if level_origin <= logging.WARNING:
																					with CaptureLogger(__UpperCAmelCase						) as cl:
																												logger.warning(__UpperCAmelCase						)
																					self.assertEqual(cl.out    ,						msg + '''\n'''						)

														# this is setting the level for all of `transformers.*` loggers
														logging.set_verbosity_error()

														# should not be able to log warnings
														with CaptureLogger(__UpperCAmelCase						) as cl:
																					logger.warning(__UpperCAmelCase						)
														self.assertEqual(cl.out    ,						''''''						)

														# should be able to log warnings again
														logging.set_verbosity_warning()
														with CaptureLogger(__UpperCAmelCase						) as cl:
																					logger.warning(__UpperCAmelCase						)
														self.assertEqual(cl.out    ,						msg + '''\n'''						)

														# restore to the original level
														logging.set_verbosity(__UpperCAmelCase						)




							@mockenv(TRANSFORMERS_VERBOSITY='''error'''						)
							def       snake_case			(					self						)		->       Optional[int]:
														# reset for the env var to take effect, next time some logger call is made
														transformers.utils.logging._reset_library_root_logger()
														# this action activates the env var
														A      :					int      		=					logging.get_logger('''transformers.models.bart.tokenization_bart'''						)

														A      :					Any      		=					os.getenv('''TRANSFORMERS_VERBOSITY'''    ,						__UpperCAmelCase						)
														A      :					List[str]      		=					logging.log_levels[env_level_str]

														A      :					Optional[int]      		=					logging.get_verbosity()
														self.assertEqual(
														    __UpperCAmelCase    ,						__UpperCAmelCase    ,						f'TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}'    ,						)

														# restore to the original level
														A      :					str      		=					''''''
														transformers.utils.logging._reset_library_root_logger()




							@mockenv(TRANSFORMERS_VERBOSITY='''super-error'''						)
							def       snake_case			(					self						)		->       Optional[int]:
														# reset for the env var to take effect, next time some logger call is made
														transformers.utils.logging._reset_library_root_logger()
														A      :					str      		=					logging.logging.getLogger()
														with CaptureLogger(__UpperCAmelCase						) as cl:
																					# this action activates the env var
																					logging.get_logger('''transformers.models.bart.tokenization_bart'''						)
														self.assertIn('''Unknown option TRANSFORMERS_VERBOSITY=super-error'''    ,						cl.out						)

														# no need to restore as nothing was changed






							def       snake_case			(					self						)		->       Optional[int]:
														# testing `logger.warning_advice()`
														transformers.utils.logging._reset_library_root_logger()

														A      :					Union[str, Any]      		=					logging.get_logger('''transformers.models.bart.tokenization_bart'''						)
														A      :					Optional[int]      		=					'''Testing 1, 2, 3'''

														with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS='''1'''						):
																					# nothing should be logged as env var disables this method
																					with CaptureLogger(__UpperCAmelCase						) as cl:
																												logger.warning_advice(__UpperCAmelCase						)
																					self.assertEqual(cl.out    ,						''''''						)

														with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS=''''''						):
																					# should log normally as TRANSFORMERS_NO_ADVISORY_WARNINGS is unset
																					with CaptureLogger(__UpperCAmelCase						) as cl:
																												logger.warning_advice(__UpperCAmelCase						)
																					self.assertEqual(cl.out    ,						msg + '''\n'''						)






def        snake_case__		(    ):
							disable_progress_bar()
							assert are_progress_bars_disabled()

							enable_progress_bar()
							assert not are_progress_bars_disabled()






